code: def he_init(m):
      s = np.sqrt(2.0 / m.in_features)
      m.weight.data.normal_(0, s)
  
imports: import logging
  import os
  from typing import List
  import numpy
  import torch
  import torch.nn
  from pythae.data.preprocessors import DataProcessor
  from pythae.models import VAMP, AutoModel, VAMPConfig
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.nn import BaseDecoder, BaseEncoder
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
label_desc: Use image node_id 1 for calling a global function with example usage: he_init(m) without return types